Detecting subtle signs of depression with automated speech analysis in a non-clinical sample.

ABSTRACT:

Background

Automated speech analysis has gained increasing attention to help diagnosing depression. Most previous studies, however, focused on comparing speech in patients with major depressive disorder to that in healthy volunteers. An alternative may be to associate speech with depressive symptoms in a non-clinical sample as this may help to find early and sensitive markers in those at risk of depression.

Methods

We included n = 118 healthy young adults (mean age: 23.5 ± 3.7 years; 77% women) and asked them to talk about a positive and a negative event in their life. Then, we assessed the level of depressive symptoms with a self-report questionnaire, with scores ranging from 0-60. We transcribed speech data and extracted acoustic as well as linguistic features. Then, we te

SUBMITTER: Konig A 

PROVIDER: S-EPMC9793349 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature